Characteristic Region-Based Image Steganography

  • Abid Yahya


For most of the current steganography techniques, the information-hiding process modifies almost all cover components. Hiding data in the whole image may affect visual quality and increases the possibility of data loss after any possible attacks. In this chapter, a new region-based steganography method, CR-BIS, which hides data in the robust regions of the image, is proposed. First, the secret data are encrypted via a highly secure encryption algorithm. Second, SURF is used to locate the strongest sections in the image. Then data embedding is accomplished in a content-based style by varying the wavelet transform coefficients of those strong sections. The robustness of the proposed algorithm increases when second-level DWT is used to hide data, especially against JPEG compression. However, applying the same scheme to the median and the low-pass filters remains difficult. Utilizing higher DWT levels is useful to enhance the robustness.


  1. Abdul-mahdi, N. H., Yahya, A., Ahmad, R. B., & Al-Qershi, O. M. (2013). Secured and robust information hiding scheme. Procedia Engineering Journal, 53, 463–471.CrossRefGoogle Scholar
  2. Bauer, J., Sünderhauf, N., & Protzel, P. (2006). Comparing several implementations of two recently published feature detectors. Paper presented at the International Conference on Intelligent Autonomous Vehicles, Toulouse, France.Google Scholar
  3. Bay, H. (2006). From wide-baseline point and line correspondences to 3D. PhD Doctoral and Habilitation Thesis Swiss Federal Institute of Technology, ETH Zurich, Zürich.Google Scholar
  4. Cover, K. S. (2006). Multiexponential reconstruction algorithm immune to false positive peak detection. Review of Scientific Instruments, 77(7), 075101–075115.CrossRefGoogle Scholar
  5. Cheddad, A., Condell, J., Curran, K., & Mc Kevitt, P. (2009). A skin tone detection algorithm for an adaptive approach to steganography. Signal Processing, 89(12), 2465–2478.CrossRefGoogle Scholar
  6. Cheddad, A., Condell, J., Curran, K., & McKevitt, P. (2008a, March 31–April 4). Biometric inspired digital image steganography. Paper presented at the Engineering of Computer Based Systems, 2008. ECBS 2008. 15th Annual IEEE International Conference and Workshop on the.Google Scholar
  7. Cheddad, A., Condell, J., Curran, K., & McKevitt, P. (2008b, May 28–30). Enhancing steganography in digital images. Paper presented at the Computer and Robot Vision, 2008. CRV ’08. Canadian Conference on.Google Scholar
  8. Cheddad, A., Condell, J., Curran, K., & Kevitt, P. M. (2010). Digital image steganography: Survey and analysis of current methods. Signal Processing, 90(3), 727–752.CrossRefGoogle Scholar
  9. Daemen, J., & Rijmen, V. (2002). The design of Rijndael: AES - the advanced encryption standard; with 17 tables. Berlin [u.a.]: Springer.Google Scholar
  10. Finch, P. J. M. (1995). A study of the Blowfish encryption algorithm. New York: City University of New York.Google Scholar
  11. Hamid, N., Yahya, A., Ahmad, R. B., & Al-Qershi, O. M. (2012a). Image steganography techniques: An overview. International Journal of Computer Science and Security (IJCSS), 6(3), 168–178.Google Scholar
  12. Hamid, N., Yahya, A., Ahmad, R. B., & Al-Qershi, O. M. (2012b, April 10–12). Characteristic region based image steganography using speeded-up robust features technique. Paper presented at the 1st International Conference on Future Communication Network (ICFCN’12). IEEE International Conference, Iraq, Baghdad.Google Scholar
  13. Hamid, N., Yahya, A., Ahmad, R. B., Najim, D., & Kanaan, L. (2013a). Steganography in image files: A survey. Australian Journal of Basic and Applied Sciences, 7(1), 35–55.Google Scholar
  14. Hamid, N., Yahya, A., Ahmad, R. B., Najim, D., & Kanaan, L. (2013b). Enhancing the robustness of digital image steganography using ECC and redundancy. WULFENIA Journal, 20(4), 153–169.Google Scholar
  15. Juan, L., & Gwun, O. (2009). A comparison of SIFT, PCA-SIFT and SURF. International Journal of Image Processing (IJIP), 3(4), 143–152.Google Scholar
  16. Karthigai Kumar, P., & Baskaran, K. (2010). An ASIC implementation of low power and high throughput blowfish crypto algorithm. Microelectronics Journal, 41(6), 347–355.CrossRefGoogle Scholar
  17. Koenderink, J. J. (1984). The structure of images. Biological Cybernetics, 50, 363–370.MathSciNetCrossRefGoogle Scholar
  18. Kruus, P., Scace, C., Heyman, M., & Mundy, M. (2003). A survey of steganographic techniques for image files. Advanced Security Research Journal, V(I), 41–52.Google Scholar
  19. Kumar, M. A., & Karthikeyan, S. (2012). Investigating the efficiency of Blowfish and Rejindael (AES) algorithms. I. J. Computer Network and Information Security, 4(2), 22–28.CrossRefGoogle Scholar
  20. Kumar, V., & Kumar, D. (2010). In V. V. Das & R. Vijaykumar (Eds.), Digital image steganography based on combination of DCT and DWT information and communication technologies (Vol. 101, pp. 596–601). Berlin Heidelberg: Springer.Google Scholar
  21. Lindeberg, T. (1990). Scale-space for discrete signals. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12(3), 234–254.CrossRefGoogle Scholar
  22. Li, L., Qian, J., & Pan, J. S. (2011). Characteristic region based watermark embedding with RST invariance and high capacity. AEU - International Journal of Electronics and Communications, 65(5), 435–442.CrossRefGoogle Scholar
  23. Li, Y., Li, C.-T., & Wei, C.-H. (2007). Protection of mammograms using blind steganography and watermarking. Paper presented at the Proceedings of the Third International Symposium on Information Assurance and Security.Google Scholar
  24. Lowe, D. G. (2004). Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60(2), 91–110.CrossRefGoogle Scholar
  25. Ming-Kuei, H. (1962). Visual pattern recognition by moment invariants. IRE Transactions on Information Theory, 8(2), 179–187.CrossRefGoogle Scholar
  26. Milad, A. A., Muda, H. Z., Noh, Z. A. B. M., & Algaet, M. A. (2012). Comparative study of performance in cryptography algorithms (Blowfish and Skipjack). Journal of Computer Science, 8(7), 1191–1197.CrossRefGoogle Scholar
  27. Potdar, V. M., Han, S., & Chang, E. (2005, August 10–12). A survey of digital image watermarking techniques. Paper presented at the Industrial Informatics, 2005. INDIN '05. 2005 3rd IEEE International Conference on.Google Scholar
  28. Rijmen, V. (1997). Cryptanalysis and design of iterated block ciphers. Ph.D. Dissertation, Katholieke Universiteit Leuven, Belgian.Google Scholar
  29. Schneier, B. (1994). Description of a newvariable-length key, 64-bit block cipher (Blowfish) Lecture notes in computer science (Vol. 809). Berlin, Heidelberg: Springer.zbMATHGoogle Scholar
  30. Schneier, B. (1995). Applied cryptography: Protocols, algorithms, and source code in C. John Wiley & Sons, Inc.Google Scholar
  31. Schneier, B. (2012). Liars and outliers: enabling the trust that society needs to thrive. ISBN: 978-1-118-14330-8. Indianapolis, IN: John Wiley & Sons, Inc.Google Scholar
  32. Singh, G., Singla, A. K., & Sandha, K. S. (2012). Superiority of blowfish algorithm in wireless networks. International Journal of Computer Applications, 44(11), 23–26.CrossRefGoogle Scholar
  33. Silva, E. A., & Agaian, S. S. (2004). The best transform in the replacement coefficients and the size of the payload relationship sense. Paper presented at the Society for Imaging Science & Technology, 2004, USA.Google Scholar
  34. Teague, M. R. (1980). Image analysis via the general theory of moments*. Journal of the Optical Society of America, 70(8), 920–930.MathSciNetCrossRefGoogle Scholar
  35. Tingyuan, N., Chuanwang, S., & Xulong, Z. (2010, April 23–25). Performance evaluation of DES and Blowfish algorithms. Paper presented at the Biomedical Engineering and Computer Science (ICBECS), 2010 International Conference on.Google Scholar
  36. Verma, H. K., & Singh, R. K. (2012). Performance analysis of RC5, Blowfish and DES block cipher algorithms. International Journal of Computer Applications, 42(16), 8–14.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Abid Yahya
    • 1
  1. 1.Faculty of Engineering & TechnologyBotswana International University of Science and TechnologyPalapyeBotswana

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